Processed Saccharomyces cerevisiae transcriptomics and genomics data for machine learning

Genomic data including open reading frame (ORF) boundaries of Saccharomyces cerevisiae C288 was obtained from the Saccharomyces Genome Database (https://www.yeastgenome.org/) (Cherry, J. M. et al. Saccharomyces Genome Database: the genomics resource of budding yeast. Nucleic Acids Res. 40, D700–5 (2012)) and published data (Xu, Z. et al. Bidirectional promoters generate pervasive transcription in yeast. Nature 457, 1033–1037 (2009), Nagalakshmi, U. et al. The transcriptional landscape of the yeast genome defined by RNA sequencing. Science 320, 1344–1349 (2008)). Coding regions were extracted based on ORF boundaries and codon frequencies were normalized to probabilities. Processed raw RNA sequencing Star counts were obtained from the Digital Expression Explorer V2 database (http://dee2.io/index.html) (Ziemann, M., Kaspi, A. & El-Osta, A. Digital expression explorer 2: a repository of uniformly processed RNA sequencing data. GigaScience vol. 8 (2019)) and filtered for experiments that passed quality control. Raw mRNA data were transformed to transcripts per million (TPM) counts and genes with zero mRNA output (TPM < 5) were removed. Prior to modeling, the mRNA counts were Box-Cox transformed.